A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design
Metamodeling is becoming a rather popular means to approximate the expensive
simulations in today's complex engineering design problems since accurate metamodels …
simulations in today's complex engineering design problems since accurate metamodels …
A critical review on intelligent optimization algorithms and surrogate models for conventional and unconventional reservoir production optimization
Aiming to find the most suitable development schemes of conventional and unconventional
reservoirs for maximum energy supply or economic benefits, reservoir production …
reservoirs for maximum energy supply or economic benefits, reservoir production …
Training effective deep reinforcement learning agents for real-time life-cycle production optimization
Life-cycle production optimization aims to obtain the optimal well control scheme at each
time control step to maximize financial profit and hydrocarbon production. However …
time control step to maximize financial profit and hydrocarbon production. However …
A new adaptive sequential sampling method to construct surrogate models for efficient reliability analysis
NC Xiao, MJ Zuo, C Zhou - Reliability Engineering & System Safety, 2018 - Elsevier
Surrogate models are often used to alleviate the computational burden for structural systems
with expensively time-consuming simulations. In this paper, a new adaptive surrogate model …
with expensively time-consuming simulations. In this paper, a new adaptive surrogate model …
Multifidelity genetic transfer: an efficient framework for production optimization
Production optimization led by computing intelligence can greatly improve oilfield economic
effectiveness. However, it is confronted with huge computational challenge because of the …
effectiveness. However, it is confronted with huge computational challenge because of the …
Global and local surrogate-model-assisted differential evolution for waterflooding production optimization
Surrogate models, which have become a popular approach to oil‐reservoir production‐
optimization problems, use a computationally inexpensive approximation function to replace …
optimization problems, use a computationally inexpensive approximation function to replace …
Multi-objective optimization of reservoir development strategy with hybrid artificial intelligence method
Optimization of subsurface hydrocarbon production holds paramount importance for
decision-makers as it determines crucial development strategies such as optimal well …
decision-makers as it determines crucial development strategies such as optimal well …
A recurrent neural network–based proxy model for well-control optimization with nonlinear output constraints
YD Kim, LJ Durlofsky - SPE Journal, 2021 - onepetro.org
In well-control optimization problems, the goal is to determine the time-varying well settings
that maximize an objective function, which is often the net present value (NPV). Various …
that maximize an objective function, which is often the net present value (NPV). Various …
胜利油田勘探开发大数据及人工智能技术应用进展.
杨勇 - Petroleum Geology & Recovery Efficiency, 2022 - search.ebscohost.com
针对勘探开发业务流程及热点问题, 阐述了大数据及人工智能技术的研究及应用进展.
经过持续攻关研究, 在胜利油田油气勘探方面形成了断层检测, 层位提取, 岩性识别 …
经过持续攻关研究, 在胜利油田油气勘探方面形成了断层检测, 层位提取, 岩性识别 …
A review of proxy modeling highlighting applications for reservoir engineering
Numerical models can be used for many purposes in oil and gas engineering, such as
production optimization and forecasting, uncertainty analysis, history matching, and risk …
production optimization and forecasting, uncertainty analysis, history matching, and risk …